Number balancing is as hard as minkowski’s theorem and shortest vector

4Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The number balancing (NBP) problem is the following: given real numbers a1, ⋯, a∑n ∈ [0, 1], find two disjoint subsets I1, I2 ⊆ [n] so that the difference (formula presented) of their sums is minimized. An application of the pigeonhole principle shows that there is always a solution where the difference is at most O(√n/2n). Finding the minimum, however, is NP-hard. In polynomial time, the differencing algorithm by Karmarkar and Karp from 1982 can produce a solution with difference at most n−Θ(logn), but no further improvement has been made since then. In this paper, we show a relationship between NBP and Minkowski’s Theorem. First we show that an approximate oracle for Minkowski’s Theorem gives an approximate NBP oracle. Perhaps more surprisingly, we show that an approximate NBP oracle gives an approximate Minkowski oracle. In particular, we prove that any polynomial time algorithm that guarantees a solution of difference at most 2√n/2n would give a polynomial approximation for Minkowski as well as a polynomial factor approximation algorithm for the Shortest Vector Problem.

Cite

CITATION STYLE

APA

Hoberg, R., Ramadas, H., Rothvoss, T., & Yang, X. (2017). Number balancing is as hard as minkowski’s theorem and shortest vector. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10328 LNCS, pp. 254–266). Springer Verlag. https://doi.org/10.1007/978-3-319-59250-3_21

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free